Senior ML Engineer, Biologics Discovery AI Ops

jj; Madrid; Presencial; EUR 55.000 - 88.000; Jornada completa

Descripción de la vacante

Johnson & Johnson Innovative Medicine seeks a Senior ML Engineer for the Biologics Discovery Data Science team. You will deploy and govern ML/AI solutions, enabling model-ready data to production workflows and ensuring reliable, scalable AI capabilities for discovery.

You will collaborate with data scientists, discovery scientists, and partner teams to operationalize models, maintain governance, and support production deployments across AI/ML environments.

Formación

• Degree in Computer Science, Engineering, Data Science, ML, or related field.
• 4+ years operationalizing and scaling AI/ML in production.
• Strong Python skills for AI/ML workflows (training, fine-tuning, deployment).
• Experience with cloud platforms and data platforms for AI/ML workloads.
• Experience with model registries and experiment tracking (MLflow, Weights & Biases).

Responsabilidades

• Build and operate scalable pipelines that deliver model-ready data to ML, generative AI, and agentic workflows.
• Ensure newly generated data can be captured, governed, and made available to downstream modeling and evaluation.
• Establish reliable deployment, serving, monitoring, access management, and lifecycle management across environments.
• Implement model, data, and workflow versioning with reproducible releases and traceability.
• Monitor ML workflows, models, and AI services for performance and reliability.

Conocimientos

Python

ML workflows

CI/CD

Cloud

ML lifecycle

Containers

Educación

BS in CS/Engineering/Data Science

Herramientas

MLflow

Weights & Biases

Descripción del empleo

Johnson & Johnson Innovative Medicine seeks a Senior ML Engineer for the Biologics Discovery Data Science team. You will deploy and govern ML/AI solutions, enabling model-ready data to production workflows and ensuring reliable, scalable AI capabilities for discovery.

You will collaborate with data scientists, discovery scientists, and partner teams to operationalize models, maintain governance, and support production deployments across AI/ML environments.